Senior Analytics Engineer

Senior Analytics Engineer at Rituals

Are you excited to be part of our dynamic team where business meets technology? Driving Rituals' growth through innovative tools within our Tech & Data department.

Share your talents

Are you passionate about translating complex business questions into robust, scalable data solutions? Rituals is on a journey of data-driven transformation, and we are looking for a Senior Analytics Engineer to be a cornerstone of our growing team. If you thrive on building impactful data products and elevating the engineering craft of your team, we’d love to have you join us.

Role Purpose

As a Senior Analytics Engineer, you will design, build, and maintain the scalable data models and pipelines that empower our business with reliable, high-quality insights. You are a leader within your squad, bridging the gap between business stakeholders and our Analytical Data Hub. You will not only deliver technically excellent solutions but also mentor others and take ownership of the squad's engineering standards, driving quality and continuous improvement from the ground up. Next to building the foundation of insights through the Analytical Data Hub, you will be enabling the vision of conversational analytics at Rituals.

Key Responsibilities

• Independently lead the solution design and iterative development of complex data marts, data domains, and end-to-end data solutions, from initial stakeholder intake to production-ready code in dbt.
• Collaborate closely with business stakeholders, reporting specialists and analysts to deeply understand their evolving needs, define KPIs, and translate them into clear, effective data products.
• Build, maintain, and optimize robust and scalable data pipelines in our GCP environment, primarily using BigQuery, dbt, and Cloud Composer (Airflow), embracing incremental delivery and feedback loops.
• Champion and implement software engineering best practices within your squad and the rest of the Analytics Engineering team. Lead discussions and set the standard together with the staff engineer for testing strategies, naming conventions, CI/CD, and release processes.
• Drive and champion an "everything-as-code" philosophy, applying it to our infrastructure, monitoring, data contracts, and documentation, ensuring adaptability and responsiveness.
• Mentor other engineers (e.g. through thoughtful code reviews or technical guidance), fostering a culture of agile learning to help level up the entire team.
• Take the lead in investigating complex data issues, conducting root cause analyses, and facilitating post-mortems to drive continuous improvement in our products and processes.
• Ensure data quality, cost-efficiency, governance, and performance are embedded into every solution you build.

Bring all of you

• 5–8 years of experience in data engineering or analytics engineering.
• Deep expertise in SQL, data modeling for analytics and python, with a strong understanding of how to meet business needs.
• Extensive hands-on experience with modern data stack technologies, particularly dbt.
• Proven experience with a cloud data warehouse (GCP BigQuery preferred) and workflow orchestration tools (Airflow/Cloud Composer preferred).
• Excellent communication and stakeholder management skills, with a proven ability to explain complex data concepts to non-technical audiences.
• A genuine passion for data modeling and understanding the "why" behind business requests.
• Demonstrable experience in leading technical designs and mentoring other engineers.
• A strong belief in engineering craftsmanship, continuous improvement, and a collaborative team culture.
• Experience with and a strong commitment to an 'everything-as-code' culture (e.g., Infrastructure as Code (Terraform), CI/CD, automated governance).

Benefits of working at Rituals

• Unique opportunities for personal and professional growth
• Staff discount on Rituals products
• Attractive bonus
• Flexible working hours tailored to your personal rhythm
• Company & team events

Key skills/competency

• SQL
• dbt
• BigQuery
• Cloud Composer
• Data Modeling
• GCP
• Analytics Engineering
• Data Pipelines
• Stakeholder Management
• Python